PROJECT SUMMARY/ABSTRACT The goals of this proposal are to develop reproducible radiographic phenotypes of pulmonary sarcoidosis and integrate radiographic data with clinical data, genetic variants and transcriptional signatures, redefining sarcoidosis biomarkers. Our long-term goal is to use these integrative phenotypes and corresponding analytic approaches to develop 1) new objective intermediate endpoints of disease progression and 2) predictive models of disease progression to aid clinicians in clinical decision-making and researchers in trial design. Sarcoidosis is a systemic granulomatous disease, primarily involving the lungs, which affects ~ 110 thousand individuals in the United States, a prevalence which is likely underestimated. Usually diagnosed between 20-50 years of life, it results in a significant decrease in quality of life and productivity. While some individuals experience spontaneous resolution, others go on to develop severe disease. Current studies of pulmonary sarcoidosis rely on characterization of lung abnormalities based on chest x-ray, visually using the Scadding staging system. It is well recognized that there is misclassification of pulmonary disease based solely on Scadding stage. In addition, this system is not useful for treatment decisions and variably predicts disease course or prognosis. Computed tomography (CT) imaging of the lung to quantify parenchymal and other pulmonary abnormalities has offered improved disease quantification in other lung diseases (idiopathic pulmonary fibrosis and COPD-emphysema). We hypothesize that detailed radiomic analysis of lung CT images in sarcoidosis combined with visual scoring metrics will identify new, more refined, phenotypes of lung disease and that combined with clinical and transcriptomic information, will identify novel integrative disease phenotypes that can be shown, in future longitudinal studies, to predict pulmonary disease resolution or progression. In this project, we will 1) Develop a radiomic and comprehensive radiographic characterization of lung abnormalities in a large cohort of sarcoidosis patients, 2) Integrate clinical, genetic, transcriptomic and radiomic characterizations of sarcoidosis to identify predictors of radiomic features of sarcoidosis and develop new integrative phenotypes of sarcoidosis, 3) Validate the clinical and genetic associated with radiographic features and a new integrative phenotypes in a real-world clinical population, and 4) Characterize the longitudinal stability of radiographic characterizations of lung abnormalities among a retrospective cohort of 75 patients. Successful completion of this research will answer critical knowledge gaps as to how radiographic pulmonary abnormalities in sarcoidosis relate to clinical and genetic phenotypes and how to combine radiographic assessment, clinical and genetic/genomic data to identify distinct phenotypes of sarcoidosis. Ultimately, this proposal will establish new standardized phenotypes for following disease longitudinally and identifying groups on which to intervene. .